Deep learning reservoir porosity prediction based on multilayer long short-term memory network
The cost of obtaining a complete porosity value using traditional coring methods is relatively
high, and as the drilling depth increases, the difficulty of obtaining the porosity value also …
high, and as the drilling depth increases, the difficulty of obtaining the porosity value also …
S-wave velocity inversion and prediction using a deep hybrid neural network
J Wang, J Cao, S Zhao, Q Qi - Science China Earth Sciences, 2022 - Springer
The S-wave velocity is a critical petrophysical parameter in reservoir description, prestack
seismic inversion, and geomechanical analysis. However, obtaining the S-wave velocity …
seismic inversion, and geomechanical analysis. However, obtaining the S-wave velocity …
Deep learning reservoir porosity prediction using integrated neural network
J Wang, J Cao - Arabian Journal for Science and Engineering, 2022 - Springer
Reservoir porosity is a crucial factor in reservoir characterization. As the availability of cores
is limited, porosity needs to be predicted from indirect measurements like well logs …
is limited, porosity needs to be predicted from indirect measurements like well logs …
A method for well log data generation based on a spatio-temporal neural network
Well logging helps geologists find hidden oil, natural gas and other resources. However,
well log data are systematically insufficient because they can only be obtained by drilling …
well log data are systematically insufficient because they can only be obtained by drilling …
Spatiotemporal synergistic ensemble deep learning method and its application to S-wave velocity prediction
J Wang, J Cao, S Yuan, X Zhou… - IEEE Geoscience and …, 2021 - ieeexplore.ieee.org
S-wave velocity (Vs) data are crucial in prestack seismic inversion, lithology interpretation,
and fluid identification. However, most drilling wells currently lack Vs data. The use of …
and fluid identification. However, most drilling wells currently lack Vs data. The use of …
[PDF][PDF] Neural networks with the assembly organization
AD Goltsev - Kiev: Naukova Dumka, 2005 - academia.edu
Это книга об искусственных нейронных сетях. Точнее, это книга об ансамблевых
нейронных сетях, которые были названы ансамблевыми потому, что в их основе лежит …
нейронных сетях, которые были названы ансамблевыми потому, что в их основе лежит …
An adsorption isotherm identification method based on CNN-LSTM neural network
K Liu, X Xie, J Yan, S Zhang, H Zhang - Journal of Molecular Modeling, 2023 - Springer
Context The morphology of adsorption isotherms embodies a wealth of information
regarding various adsorption mechanisms, rendering the classification and identification …
regarding various adsorption mechanisms, rendering the classification and identification …
[HTML][HTML] Segmentation of visual images by sequential extracting homogeneous texture areas
The purpose of the research is to develop a universal algorithm for partial texture
segmentation of any visual images. The main peculiarity of the proposed segmentation …
segmentation of any visual images. The main peculiarity of the proposed segmentation …
A neural network with competitive layers for character recognition
A Goltsev, V Gritsenko - … Letters on Computer Vision and Image …, 2022 - elcvia.cvc.uab.cat
A structure and functioning mechanisms of a neural network with competitive layers are
described. The network is intended to solve the character recognition task. The network …
described. The network is intended to solve the character recognition task. The network …
Design of solving similarity recognition for cloth products based on fuzzy logic and particle swarm optimization algorithm
BM Chang - KSII Transactions on Internet and Information Systems …, 2017 - koreascience.kr
This paper introduces a new method to solve Similarity Recognition for Cloth Products,
which is based on Fuzzy logic and Particle swarm optimization algorithm. For convenience …
which is based on Fuzzy logic and Particle swarm optimization algorithm. For convenience …